Promises, Outlooks and Challenges of Diffusion Language Modeling

17 June 2024

Papers citing "Promises, Outlooks and Challenges of Diffusion Language Modeling"

8 / 8 papers shown

Title
Beyond Autoregression: Fast LLMs via Self-Distillation Through Time Justin Deschenaux Çağlar Gülçehre 47 2 0 28 Oct 2024
Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto Samuel L. Smith Albert Gu Anushan Fernando Çağlar Gülçehre Razvan Pascanu Soham De 88 268 0 11 Mar 2023
From Denoising Diffusions to Denoising Markov Models Joe Benton Yuyang Shi Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 74 25 0 07 Nov 2022
Concrete Score Matching: Generalized Score Matching for Discrete Data Chenlin Meng Kristy Choi Jiaming Song Stefano Ermon DiffM 192 53 0 02 Nov 2022
A Continuous Time Framework for Discrete Denoising Models Andrew Campbell Joe Benton Valentin De Bortoli Tom Rainforth George Deligiannidis Arnaud Doucet DiffM 194 134 0 30 May 2022
Diffusion-LM Improves Controllable Text Generation Xiang Lisa Li John Thickstun Ishaan Gulrajani Percy Liang Tatsunori B. Hashimoto AI4CE 173 777 0 27 May 2022
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom Didrik Nielsen P. Jaini Patrick Forré Max Welling DiffM 207 395 0 10 Feb 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 264 4,489 0 23 Jan 2020